Zobrazeno 1 - 10
of 36 747
pro vyhledávání: '"Zhang, Kai"'
Autor:
Cai, Yuanhao, Zhang, He, Zhang, Kai, Liang, Yixun, Ren, Mengwei, Luan, Fujun, Liu, Qing, Kim, Soo Ye, Zhang, Jianming, Zhang, Zhifei, Zhou, Yuqian, Lin, Zhe, Yuille, Alan
Existing feed-forward image-to-3D methods mainly rely on 2D multi-view diffusion models that cannot guarantee 3D consistency. These methods easily collapse when changing the prompt view direction and mainly handle object-centric prompt images. In thi
Externí odkaz:
http://arxiv.org/abs/2411.14384
Autor:
Chou, Gene, Zhang, Kai, Bi, Sai, Tan, Hao, Xu, Zexiang, Luan, Fujun, Hariharan, Bharath, Snavely, Noah
We address the problem of generating videos from unposed internet photos. A handful of input images serve as keyframes, and our model interpolates between them to simulate a path moving between the cameras. Given random images, a model's ability to c
Externí odkaz:
http://arxiv.org/abs/2411.13549
We propose and study several inverse boundary problems associated with a quasilinear hyperbolic equation of the form ${c(x)^{-2}}\partial_t^2u=\Delta_g(u+F(x, u))+G(x, u)$ on a compact Riemannian manifold $(M, g)$ with boundary. We show that if $F(x,
Externí odkaz:
http://arxiv.org/abs/2411.09917
Autor:
Gu, Yu, Zheng, Boyuan, Gou, Boyu, Zhang, Kai, Chang, Cheng, Srivastava, Sanjari, Xie, Yanan, Qi, Peng, Sun, Huan, Su, Yu
Language agents have demonstrated promising capabilities in automating web-based tasks, though their current reactive approaches still underperform largely compared to humans. While incorporating advanced planning algorithms, particularly tree search
Externí odkaz:
http://arxiv.org/abs/2411.06559
Autor:
Zhang, Kai-Yi, Huang, An-Jing, Tu, Kun, Li, Ming-Han, Zhang, Chi, Qi, Wei, Wu, Ya-Dong, Yu, Yu
Secure multiparty computation enables collaborative computations across multiple users while preserving individual privacy, which has a wide range of applications in finance, machine learning and healthcare. Secure multiparty computation can be reali
Externí odkaz:
http://arxiv.org/abs/2411.04558
Autor:
Sun, Xingwu, Chen, Yanfeng, Huang, Yiqing, Xie, Ruobing, Zhu, Jiaqi, Zhang, Kai, Li, Shuaipeng, Yang, Zhen, Han, Jonny, Shu, Xiaobo, Bu, Jiahao, Chen, Zhongzhi, Huang, Xuemeng, Lian, Fengzong, Yang, Saiyong, Yan, Jianfeng, Zeng, Yuyuan, Ren, Xiaoqin, Yu, Chao, Wu, Lulu, Mao, Yue, Xia, Jun, Yang, Tao, Zheng, Suncong, Wu, Kan, Jiao, Dian, Xue, Jinbao, Zhang, Xipeng, Wu, Decheng, Liu, Kai, Wu, Dengpeng, Xu, Guanghui, Chen, Shaohua, Chen, Shuang, Feng, Xiao, Hong, Yigeng, Zheng, Junqiang, Xu, Chengcheng, Li, Zongwei, Kuang, Xiong, Hu, Jianglu, Chen, Yiqi, Deng, Yuchi, Li, Guiyang, Liu, Ao, Zhang, Chenchen, Hu, Shihui, Zhao, Zilong, Wu, Zifan, Ding, Yao, Wang, Weichao, Liu, Han, Wang, Roberts, Fei, Hao, Yu, Peijie, Zhao, Ze, Cao, Xun, Wang, Hai, Xiang, Fusheng, Huang, Mengyuan, Xiong, Zhiyuan, Hu, Bin, Hou, Xuebin, Jiang, Lei, Ma, Jianqiang, Wu, Jiajia, Deng, Yaping, Shen, Yi, Wang, Qian, Liu, Weijie, Liu, Jie, Chen, Meng, Dong, Liang, Jia, Weiwen, Chen, Hu, Liu, Feifei, Yuan, Rui, Xu, Huilin, Yan, Zhenxiang, Cao, Tengfei, Hu, Zhichao, Feng, Xinhua, Du, Dong, Yu, Tinghao, Tao, Yangyu, Zhang, Feng, Zhu, Jianchen, Xu, Chengzhong, Li, Xirui, Zha, Chong, Ouyang, Wen, Xia, Yinben, Li, Xiang, He, Zekun, Chen, Rongpeng, Song, Jiawei, Chen, Ruibin, Jiang, Fan, Zhao, Chongqing, Wang, Bo, Gong, Hao, Gan, Rong, Hu, Winston, Kang, Zhanhui, Yang, Yong, Liu, Yuhong, Wang, Di, Jiang, Jie
In this paper, we introduce Hunyuan-Large, which is currently the largest open-source Transformer-based mixture of experts model, with a total of 389 billion parameters and 52 billion activation parameters, capable of handling up to 256K tokens. We c
Externí odkaz:
http://arxiv.org/abs/2411.02265
Autor:
Lou, Renze, Xu, Hanzi, Wang, Sijia, Du, Jiangshu, Kamoi, Ryo, Lu, Xiaoxin, Xie, Jian, Sun, Yuxuan, Zhang, Yusen, Ahn, Jihyun Janice, Fang, Hongchao, Zou, Zhuoyang, Ma, Wenchao, Li, Xi, Zhang, Kai, Xia, Congying, Huang, Lifu, Yin, Wenpeng
Numerous studies have assessed the proficiency of AI systems, particularly large language models (LLMs), in facilitating everyday tasks such as email writing, question answering, and creative content generation. However, researchers face unique chall
Externí odkaz:
http://arxiv.org/abs/2410.22394
Autor:
Jin, Haian, Jiang, Hanwen, Tan, Hao, Zhang, Kai, Bi, Sai, Zhang, Tianyuan, Luan, Fujun, Snavely, Noah, Xu, Zexiang
We propose the Large View Synthesis Model (LVSM), a novel transformer-based approach for scalable and generalizable novel view synthesis from sparse-view inputs. We introduce two architectures: (1) an encoder-decoder LVSM, which encodes input image t
Externí odkaz:
http://arxiv.org/abs/2410.17242
Color video snapshot compressive imaging (SCI) employs computational imaging techniques to capture multiple sequential video frames in a single Bayer-patterned measurement. With the increasing popularity of quad-Bayer pattern in mainstream smartphone
Externí odkaz:
http://arxiv.org/abs/2410.14214
Large Language Models (LLMs) have shown remarkable capabilities in various natural language processing tasks. However, LLMs may rely on dataset biases as shortcuts for prediction, which can significantly impair their robustness and generalization cap
Externí odkaz:
http://arxiv.org/abs/2410.13343